An autonomous architecture based on reinforcement deep neural network for resource allocation in cloud computing

Implementation of Precision Machine Tool Thermal Error Compensation in Edge-Cloud-Fog Computing Architecture

(2023) Lin Zhang et al.   JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME

Mobility Aware-Task Scheduling and Virtual Fog for Offloading in IoT-Fog-Cloud Environment

(2023) Khaled M. Matrouk et al.   WIRELESS PERSONAL COMMUNICATIONS

Fog computing for next-generation Internet of Things: Fundamental, state-of-the-art and research challenges

(2023) Abhishek Hazra et al.   Computer Science Review

A solution for resource allocation through complex systems in fog computing for the internet of things

(2023) Fatimah Faraji et al.   COMPUTING

Meta-heuristic Based Hybrid Service Placement Strategies for Two-Level Fog Computing Architecture

(2022) B. V. Natesha et al.   Journal of Network and Systems Management

Improving Source location privacy in social Internet of Things using a hybrid phantom routing technique

(2022) Tariq Hussain et al.   COMPUTERS & SECURITY

Stable and efficient resource management using deep neural network on cloud computing

(2022) Byeonghui Jeong et al.   NEUROCOMPUTING

IMPROVED RESOURCE MANAGEMENT AND UTILIZATION BASED ON A FOG-CLOUD COMPUTING SYSTEM WITH IOT INCORPORATED WITH CLASSIFIER SYSTEMS

(2021) M. Buvana et al.   MICROPROCESSORS AND MICROSYSTEMS

Blockchain-Based Security Mechanism for the Medical Data at Fog Computing Architecture of Internet of Things

(2021) Desire Ngabo et al.   Electronics

A Review on Fog Computing: Architecture, Fog with IoT, Algorithms and Research Challenges

(2021) Sabireen H. et al.   ICT Express

HUNTER: AI based holistic resource management for sustainable cloud computing

(2021) Shreshth Tuli et al.   JOURNAL OF SYSTEMS AND SOFTWARE

Smart healthcare IoT applications based on fog computing: architecture, applications and challenges

(2021) Vu Khanh Quy et al.   Complex & Intelligent Systems

An efficient load balancing system using adaptive dragonfly algorithm in cloud computing

(2020) P. Neelima et al.   Cluster Computing-The Journal of Networks Software Tools and Applications

Efficient resource management and workload allocation in fog–cloud computing paradigm in IoT using learning classifier systems

(2020) Mahdi Abbasi et al.   COMPUTER COMMUNICATIONS

Dynamic resource allocation with optimized task scheduling and improved power management in cloud computing

(2020) J. Praveenchandar et al.   Journal of Ambient Intelligence and Humanized Computing

Holistic resource management for sustainable and reliable cloud computing: An innovative solution to global challenge

(2019) Sukhpal Singh Gill et al.   JOURNAL OF SYSTEMS AND SOFTWARE

Fog computing architecture for personalized recommendation of banking products

(2019) Elena Hernández-Nieves et al.   EXPERT SYSTEMS WITH APPLICATIONS

Fog Computing Architecture, Evaluation, and Future Research Directions

(2018) Mohammad Aazam et al.   IEEE COMMUNICATIONS MAGAZINE

Survey on fog computing: architecture, key technologies, applications and open issues

(2017) Pengfei Hu et al.   JOURNAL OF NETWORK AND COMPUTER APPLICATIONS

Load-balancing algorithms in cloud computing: A survey

(2017) Einollah Jafarnejad Ghomi et al.   JOURNAL OF NETWORK AND COMPUTER APPLICATIONS

A Framework of Fog Computing: Architecture, Challenges, and Optimization

(2017) Yang Liu et al.   IEEE Access

IFCIoT: Integrated Fog Cloud IoT: A novel architectural paradigm for the future Internet of Things.

(2017) Arslan Munir et al.   IEEE Consumer Electronics Magazine

Particle swarm optimization (PSO). A tutorial

(2015) Federico Marini et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Cloud computing and education: A state-of-the-art survey

(2015) José A. González-Martínez et al.   COMPUTERS & EDUCATION

Resource management in cloud computing: Taxonomy, prospects, and challenges

(2015) Saad Mustafa et al.   COMPUTERS & ELECTRICAL ENGINEERING

Cloud Computing

(2014) Toni Mastelic et al.   ACM COMPUTING SURVEYS